Big Data, Bigger Marketing

Big data refers to the ever-increasing volume, velocity, variety, variability and complexity of information. For marketing organizations, big data is the fundamental consequence of the new marketing landscape, born from the digital world we now live in.

The term "big data" doesn’t just refer to the data itself; it also refers to the challenges, capabilities and competencies associated with storing and analyzing such huge data sets to support a level of decision making that is more accurate and timely than anything previously attempted – big-data-driven decision making.

Many marketers may feel like data has always been big – and in some ways, it has. But think about the customer data businesses collected 20 years ago – point of sale transaction data, responses to direct mail campaigns, coupon redemption, etc. Then think about the customer data collected today – online purchase data, click-through rates, browsing behavior, social media interactions, mobile device usage, geolocation data, etc. Comparatively speaking, there’s no comparison. And to borrow an old phrase, "You ain’t seen nothin' yet."

Why big data matters to marketing

Having big data doesn’t automatically lead to better marketing – but the potential is there. Think of big data as your secret ingredient, your raw material, your essential element. It’s not the data itself that’s so important. Rather, it’s the insights derived from big data, the decisions you make and the actions you take that make all the difference.

By combining big data with an integrated marketing management strategy, marketing organizations can make a substantial impact in these key areas:

Customer engagement. Big data can deliver insight into not just who your customers are, but where they are, what they want, how they want to be contacted and when.

Customer retention and loyalty. Big data can help you discover what influences customer loyalty and what keeps them coming back again and again.

Marketing optimization/performance. With big data, you can determine the optimal marketing spend across multiple channels, as well as continuously optimize marketing programs through testing, measurement and analysis.

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More on big data in marketing

Three types of big data that are a big deal for marketing

Customer: The big data category most familiar to marketing may include behavioral, attitudinal and transactional metrics from such sources as marketing campaigns, points of sale, websites, customer surveys, social media, online communities and loyalty programs.

Financial: Typically housed in an organization’s financial systems, this big data category may include sales, revenue, profits and other objective data types that measure the financial health of the organization.

Challenges

The challenges related to the effective use of big data can be especially daunting for marketing. That's because most analytics systems are not aligned to the marketing organization’s data, processes and decisions. For marketing, three of the biggest challenges are:

Knowing what data to gather. Data, data everywhere. You have enormous volumes of customer, operational and financial data to contend with. But more is not necessarily better – it has to be the right data.

Knowing which analytical tools to use. As the volume of big data grows, the time available for making decisions and acting on them is shrinking. Analytical tools can help you aggregate and analyze data, as well as allocate relevant insights and decisions appropriately throughout the organization – but which ones?

Knowing how to go from data to insight to impact. Once you have the data, how do you turn it into insight? And how do you use that insight to make a positive impact on your marketing programs?

Three steps for going from big data to better marketing

Big data is a big deal in marketing. But there are a few things every marketer should keep in mind to help ensure that big data will lead to big success:

Use big data to dig for deeper insight. Big data affords you the opportunity to dig deeper and deeper into the data, peeling back layers to reveal richer insights. The insights you gain from your initial analysis can be explored further, with richer, deeper insights emerging each time. This level of insight can help you develop specific strategies and actions to drive growth.

Get insights from big data to those who can use it. There’s no debating it – CMOs need the meaningful insights that big data can provide; but so do front-line store managers, and call center phone staff, and sales associates, and so on and so on. What good is insight if it stays within the confines of the board room? Get it into the hands of those who can act on it.

Don’t try to save the world – at least not at first. Taking on big data can at times seem overwhelming, so start out by focusing on a few key objectives. What outcomes would you like to improve? Once you decide that, you can identify what data you would need to support the related analysis. When you’ve completed that exercise, move on to your next objective. And the next.